What Do You Get when You Mix AI, PR, and HR?
Similar Posts
Algorithmic Accountability Act for AI Product Managers: Sections 6 through 11
Sections 6 through 11 of the Algorithmic Accountability Act (2022 and 2023) have less practical implications for product management. They ensure that the Act, if passed, becomes part of the Federal Trade Commission Act, as well as introduce requirements that the FTC needs to meet when implementing the Act. This text follows my notes on…
Business Risks of IP Compliance Requirements for Generative AI
IP compliance requirements on generative AI reduce the readily and cheaply available amount of training data, with a few consequences on how product development and product operations are done.
Data Authenticity, Accuracy, Objectivity, and Diversity Requirements in Generative AI
In April 2023, the Cyberspace Administration of China released a draft Regulation for Generative Artificial Intelligence Services. The note below continues the previous one related to the same regulation, here. One of the requirements on Generative AI is that the authenticity, accuracy, objectivity, and diversity of the data can be guaranteed. My intent below is…
AI for the sake of AI :-) L’art pour l’art
Just like l’art pour l’art, or art for the sake of art was the bohemian creed in the 19th century, it looks like there’s an “AI for the sake of AI” creed now when building general-purpose AI systems based on Large Language Models. Let’s say that the aim for a sustainable business are happy, paying,…
AI | Economics of AI | Market
What Does a Training Data Market Mean for Authors?
If any text can be training data for a Large Language Model, then any text is a training dataset that can be valued through a market for training data. Which datasets have high value? Wikipedia, StackOverflow, Reddit, Quora are examples that have value for different reasons, that is, because they can be used to train…